TalentsToday

The engagement covers solution definition, build, and launch across 15 European countries, with integrations to MuleSoft/Microsoft D365, Akeneo PIM, Adobe Experience Manager, and Stripe or Adyen for payments. The project kicks off mid-August with an intensive discovery and solution definition phase, followed by iterative build sprints and end-of-year hypercare.

Role summary

The Solution Consultant is the functional bridge between client stakeholders and the delivery team. You'll support requirements discovery, translate business needs into functional designs and user stories, and ensure the solution delivered matches what the client signed up for. This is a client-facing role requiring confident workshop facilitation and clear written communication.

Key responsibilities

• Lead and facilitate discovery workshops with client business and technical stakeholders
• Elicit, document, and validate business and functional requirements
• Author functional design documentation as part of the Solution
• Design deliverables
• Build and maintain the product backlog in Azure DevOps: epics, user stories, acceptance criteria
• Partner with the Salesforce Architect on solution decisions and trade-offs
• Support sprint ceremonies: backlog refinement, sprint planning, demo preparation, UAT coordination
• Act as day-to-day functional point of contact for the client Product Owner

• Support integration requirements definition alongside third-party integration vendors

   

Required qualifications

• 5+ years as a Solution Consultant, Functional Consultant, or
• Senior Business Analyst on ecommerce implementations
• Hands-on delivery experience with Salesforce B2B Commerce (or B2C Commerce with strong B2B exposure)
• Proven workshop facilitation and requirements documentation skills
• Experience writing user stories and managing backlogs in Azure DevOps or JIRA
• Strong understanding of ecommerce integration patterns (ERP, PIM, CMS, payments)
• Fluent English; comfortable working with US and EU stakeholders

PROJECT DESCRIPTION

Design cloud-native, resilient and scalable solutions in partnership with Architecture, Development, DevOps, and Cyber teams, implementing application security principles and culture while providing subject matter expertise on cloud services and leading engineering teams in building secure systems through best engineering practices in an Agile environment.

IN THIS ROLE, YOU WILL

• Design Azure-hosted solutions that meet business & technical requirements
• Create highly-available scalable, reliable and secure cloud environments, ensuring optimal performance
• Acts as the Azure Cloud Champion for the App Development and DevOps teams
• Ensure compliance with industry standards and firm policies
• Works with the application architects, DevSecOps and Cyber Team, to review security questionnaires
• Advocates for the Architecture, Development, DevOps, Cybersecurity, DevSecOps, and Agile engineering procedures, quality engineering practices and advanced requirement capturing techniques for improving end-to-end delivery practices
• Provide guidance to DevOps & development teams to ensure smooth integration of cloud solutions
• Organizes and coordinates infrastructure architecture reviews as needed
• Mentor and provide technical guidance to junior team members
• Liaise with vendors and cloud providers to ensure proper delivery of services
• Monitor cloud systems and ensure they meet performance benchmarks and security requirements
• Optimize cloud resources and cost through automation and monitoring
• Implement disaster recovery strategy, ensure high availability of cloud resources
• Maintain up-to-date technical documentation
• Report on cloud service performance and costs trends
  
  
  IF YOU HAVE
• Bachelor's or Master's degree in Computer Science, Information Technology or a related field
• 5+ years of experience in designing, developing & deploying cloud architecture
• Expertise in Azure Cloud platform including PaaS offerings like AKS, Azure SQL, APIM, Azure Service Bus etc
• Experience with cloud-native technologies such as containers (Docker, Kubernetes) and microservices architecture
• Strong knowledge of networking, security, and database management in cloud environment
• Knowledge of Source Code Management concepts (e.g., code lines, branching, merging, integration, versioning)
• Experience producing PoCs (Proof of Concept) to support the development and DevOps teams
• Ability to translate traditional SDLC approach (plan, code, build, test, release, deploy and monitor) to the phases of agile development when writing software to automate cloud architecture related tasks
  
  HOW’S THE HIRING PROCESS GOING
• We strive to make a smooth and transparent hiring process to find the perfect match for both sides. Steps may differ depending on the position — here’s what to expect:
• Initial Interview: If your background fits the role, we'll invite you for an interview with a Talent Acquisition Specialist.
• Technical Interview: Depending on the position, you may complete a technical assessment or test task.
• Client’s Interview:
• Final Decision: After all steps, we'll get back to you with the result and next steps.

About our Customer

it's a Denmark-based technology company working exclusively with international clients. Since 2019, we've partnered with established organizations to build high-quality digital products and scalable technology solutions. Our team values ownership, innovation, and continuous learning while maintaining a collaborative and low-management culture where everyone can make a real impact. About the Role We're looking for an AI Automation Engineer to help transform how we build, review, deploy, and operate software using AI. You'll design agentic workflows, AI-powered automation, and internal developer tools while contributing to backend development and platform engineering

Responsibilities 

• Design and implement AI-powered automation using LLMs and agentic workflows
•  Integrate AI into engineering processes, including code review, security scanning, testing, documentation, release notes, and developer copilots
• Build agentic workflows using APIs, tool/function calling, and MCP servers
• Implement guardrails, evaluations, and monitoring to ensure safe and reliable AI automation
• Develop backend features using C#/.NET when required.
• Design and maintain CI/CD pipelines using Azure DevOps YAML and GitHub Actions
• Support cloud infrastructure, Kubernetes, secrets management, scaling, and Infrastructure as Code
• Promote DevSecOps practices by integrating security into the development lifecycle
• Communicate technical risks, dependencies, and recommendations with stakeholders
• Stay up to date with the latest AI technologies and continuously improve engineering practices
   

✅Requirements

•  Hands-on experience building AI automation with LLMs, prompt engineering, agent design, tool/function calling, and AI integrations
• Practical experience evaluating, monitoring, and optimizing AI-powered solutions
• Strong experience with Azure DevOps (YAML) and/or GitHub Actions
• Solid Azure and Kubernetes (AKS) experience
• Experience with Infrastructure as Code (Terraform, Bicep, or ARM)
• Backend development experience with C#/.NET, ASP.NET Core, Entity Framework Core, and REST APIs
• Scripting experience with Python, PowerShell, or Bash
• Familiarity with DevSecOps, vulnerability scanning, and secrets management
• Experience working in Agile environments (Scrum/Kanban)
• 2+ years of software engineering experience with hands-on AI/automation projects
• Written and spoken Englis

ML Engineer / MLOps Engineer

Location: Remote
Duration: Long-term
 

Основні обов'язки:

• Керувати повним циклом розгортання, підтримки та моніторингу ML/DL-моделей у production.
• Проєктувати та впроваджувати системи керування датасетами та лейблами, включаючи versioning та інтеграцію customer feedback.
• Розвивати Model Registry з підтримкою версіонування, model lineage та локального inference.
• Впроваджувати рішення для Experiment Tracking та Monitoring (ML та Generative AI), включаючи оцінку моделей, виявлення data drift та забезпечення відтворюваності експериментів.
• Розвивати системи model serving та inference: autoscaling, A/B testing, canary deployments, оптимізація latency та вартості.
• Забезпечувати інфраструктуру для Generative AI (prompt management, tagging tools, LLM testing).
• Покращувати DevOps-процеси, автоматизувати ML workflows та впроваджувати reusable компоненти (CI/CD, data loaders, automated retraining).
• Тісно співпрацювати з Data Scientists та командою Data Platform Engineering для впровадження ML-рішень у production.
   

Основні вимоги:

• Вища освіта у сфері Computer Science, Software Engineering або суміжній галузі.
• Практичний досвід роботи як ML Engineer та MLOps Engineer.
• Глибоке розуміння ML/DL workflows та MLOps best practices.
• Досвід побудови та підтримки CI/CD процесів.
• Комерційний досвід роботи з AWS, Azure або GCP.
• Впевнене володіння Python та Java.
• Досвід роботи з PostgreSQL, MongoDB, Redis.
• Практичний досвід з MLflow, Langfuse, SageMaker або аналогічними інструментами.
• Досвід роботи зі Spark.
• Досвід використання PyTorch або TensorFlow.
   

Важливо:  мати комерційний досвід одночасно як ML Engineer, так і MLOps Engineer.

Interview Process:
1. HR with Recruiter (~30 min)

2. GenAI Avatar Screening  (~30 min)

3. Intro call with the client (~30 min)
4. Technical interview (~2 hours)
5. Second technical interview (1–1.5 hours)
6. Final HR interview with client (~30 min)